finally dirty cleaneed rpe.csv

data_preparation/rpe_processing.py

@@ -9,47 +9,56 @@ def vectorize_mult(column, dictionary, postfix, df, file=None):
     df.to_csv('cleaned/{}.csv'.format(file))
 
 
-csv = pd.read_csv("data/rpe.csv")
-vectorize_mult("Training", {"No": 0, "Yes": 1}, "", csv)
+csv = pd.read_csv("cleaned/notnormalized_with_continuousNan_rpe.csv")
+# vectorize_mult("Training", {"No": 0, "Yes": 1}, "", csv)
+#
+# mapping = {"Mobility/Recovery": 1, "Game": 0, "Skills": 0, "Conditioning": 0,
+#            "Strength": 0, "Combat": 0, "Speed": 0, np.nan: 0}
+# vectorize_mult("SessionType", mapping, "Mobility/Recovery", csv)
+# mapping["Mobility/Recovery"] = 0
+# mapping["Game"] = 1
+# vectorize_mult("SessionType", mapping, "Game", csv)
+# mapping["Game"] = 0
+# mapping["Skills"] = 1
+# vectorize_mult("SessionType", mapping, "Skills", csv)
+# mapping["Skills"] = 0
+# mapping["Conditioning"] = 1
+# vectorize_mult("SessionType", mapping, "Conditioning", csv)
+# mapping["Conditioning"] = 0
+# mapping["Strength"] = 1
+# vectorize_mult("SessionType", mapping, "Strength", csv)
+# mapping["Strength"] = 0
+# mapping["Combat"] = 1
+# vectorize_mult("SessionType", mapping, "Combat", csv)
+# mapping["Combat"] = 0
+# mapping["Speed"] = 1
+# vectorize_mult("SessionType", mapping, "Speed", csv)
+# mapping["Speed"] = 0
+# mapping[np.nan] = 1
+# vectorize_mult("SessionType", mapping, "Unknown", csv)
+# mapping[np.nan] = 0
+#
+# mapping = {"Not at all": 1, "Absolutely": 0, "Somewhat": 0, np.nan: 0}
+# vectorize_mult("BestOutOfMyself", mapping, "NotAtAll", csv)
+# mapping["Not at all"] = 0
+# mapping["Absolutely"] = 1
+# vectorize_mult("BestOutOfMyself", mapping, "Absolutely", csv)
+# mapping["Absolutely"] = 0
+# mapping["Somewhat"] = 1
+# vectorize_mult('BestOutOfMyself', mapping, "Somewhat", csv)
+# mapping["Somewhat"] = 0
+# mapping[np.nan] = 1
+# vectorize_mult('BestOutOfMyself', mapping, "Unknown", csv)
+# mapping[np.nan] = 0
+#
+# csv.to_csv("cleaned/notnormalized_with_continuousNan_rpe.csv")
 
-mapping = {"Mobility/Recovery": 1, "Game": 0, "Skills": 0, "Conditioning": 0,
-           "Strength": 0, "Combat": 0, "Speed": 0, np.nan: 0}
-vectorize_mult("SessionType", mapping, "Mobility/Recovery", csv)
-mapping["Mobility/Recovery"] = 0
-mapping["Game"] = 1
-vectorize_mult("SessionType", mapping, "Game", csv)
-mapping["Game"] = 0
-mapping["Skills"] = 1
-vectorize_mult("SessionType", mapping, "Skills", csv)
-mapping["Skills"] = 0
-mapping["Conditioning"] = 1
-vectorize_mult("SessionType", mapping, "Conditioning", csv)
-mapping["Conditioning"] = 0
-mapping["Strength"] = 1
-vectorize_mult("SessionType", mapping, "Strength", csv)
-mapping["Strength"] = 0
-mapping["Combat"] = 1
-vectorize_mult("SessionType", mapping, "Combat", csv)
-mapping["Combat"] = 0
-mapping["Speed"] = 1
-vectorize_mult("SessionType", mapping, "Speed", csv)
-mapping["Speed"] = 0
-mapping[np.nan] = 1
-vectorize_mult("SessionType", mapping, "Unknown", csv)
-mapping[np.nan] = 0
-
-mapping = {"Not at all": 1, "Absolutely": 0, "Somewhat": 0, np.nan: 0}
-vectorize_mult("BestOutOfMyself", mapping, "NotAtAll", csv)
-mapping["Not at all"] = 0
-mapping["Absolutely"] = 1
-vectorize_mult("BestOutOfMyself", mapping, "Absolutely", csv)
-mapping["Absolutely"] = 0
-mapping["Somewhat"] = 1
-vectorize_mult('BestOutOfMyself', mapping, "Somewhat", csv)
-mapping["Somewhat"] = 0
-mapping[np.nan] = 1
-vectorize_mult('BestOutOfMyself', mapping, "Unknown", csv)
-mapping[np.nan] = 0
-
-print(csv.isnull().sum())
-csv.to_csv("cleaned/notnormalized_with_continuousNan_rpe.csv")
+for i in range(len(csv.dtypes)):
+  type = csv.dtypes[i]
+  if type != "object":
+    colname = csv.columns[i]
+    if csv[colname].hasnans:
+      print(colname)
+      csv[colname] = csv[colname].fillna(0)
+#print(csv.isnull().sum())
+csv.to_csv("cleaned/notnormalized_with_0Nan_rpe.csv")